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    "rules_description": [
        "if (char_freq_%3B <= 0.183) and (word_freq_you <= 0.385) and (word_freq_george > 0.005) then class: 0 (proba: 100.0%) | based on 17 samples",
        "if (word_freq_1999 > 0.065) and (word_freq_all > 0.27) and (char_freq_%23 > 0.153) then class: 1 (proba: 100.0%) | based on 1 samples",
        "if (char_freq_%21 <= 0.186) and (word_freq_mail <= 0.025) and (word_freq_hp > 0.13) then class: 0 (proba: 98.48%) | based on 47 samples",
        "if (word_freq_data <= 0.235) and (word_freq_data > 0.015) and (word_freq_all <= 0.395) then class: 1 (proba: 100.0%) | based on 3 samples",
        "if (word_freq_report <= 0.025) and (word_freq_will > 1.99) and (word_freq_receive > 0.455) then class: 0 (proba: 80.0%) | based on 3 samples",
        "if (word_freq_order <= 0.085) and (char_freq_%21 <= 0.088) and (capital_run_length_longest > 23.0) then class: 1 (proba: 53.45%) | based on 40 samples",
        "if (word_freq_address > 0.09) and (word_freq_labs <= 0.085) and (word_freq_all <= 0.195) then class: 1 (proba: 53.33%) | based on 18 samples",
        "if (capital_run_length_longest <= 29.5) and (char_freq_%21 <= 0.142) and (word_freq_you > 1.81) then class: 0 (proba: 55.38%) | based on 41 samples",
        "if (word_freq_remove > 0.01) and (char_freq_%21 <= 0.049) and (word_freq_pm <= 0.12) then class: 1 (proba: 82.35%) | based on 12 samples",
        "if (word_freq_email > 0.055) and (capital_run_length_longest <= 15.5) and (word_freq_remove > 0.025) then class: 1 (proba: 77.78%) | based on 7 samples",
        "if (word_freq_money > 0.03) and (word_freq_addresses <= 0.015) and (word_freq_labs <= 0.065) then class: 1 (proba: 88.14%) | based on 39 samples",
        "if (word_freq_your <= 0.915) and (char_freq_%23 <= 0.01) and (word_freq_000 <= 0.145) then class: 0 (proba: 81.22%) | based on 145 samples",
        "if (capital_run_length_longest > 18.5) and (word_freq_you > 1.06) and (word_freq_order > 0.04) then class: 1 (proba: 100.0%) | based on 26 samples",
        "if (word_freq_order <= 0.025) and (word_freq_original <= 0.165) and (word_freq_credit <= 0.265) then class: 0 (proba: 56.66%) | based on 216 samples",
        "if (word_freq_telnet <= 0.075) and (word_freq_free > 0.065) and (word_freq_free <= 0.35) then class: 1 (proba: 83.78%) | based on 21 samples"
    ],
    "config": {
        "n_trees": 15,
        "max_depth": 3,
        "max_features": 2,
        "used_data": 0.1
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}